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      Population Genetic Analysis of Propionibacterium acnes Identifies a Subpopulation and Epidemic Clones Associated with Acne

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          Abstract

          The involvement of Propionibacterium acnes in the pathogenesis of acne is controversial, mainly owing to its dominance as an inhabitant of healthy skin. This study tested the hypothesis that specific evolutionary lineages of the species are associated with acne while others are compatible with health. Phylogenetic reconstruction based on nine housekeeping genes was performed on 210 isolates of P. acnes from well-characterized patients with acne, various opportunistic infections, and from healthy carriers. Although evidence of recombination was observed, the results showed a basically clonal population structure correlated with allelic variation in the virulence genes tly and camp5, with pulsed field gel electrophoresis (PFGE)- and biotype, and with expressed putative virulence factors. An unexpected geographically and temporal widespread dissemination of some clones was demonstrated. The population comprised three major divisions, one of which, including an epidemic clone, was strongly associated with moderate to severe acne while others were associated with health and opportunistic infections. This dichotomy correlated with previously observed differences in in vitro inflammation-inducing properties. Comparison of five genomes representing acne- and health-associated clones revealed multiple both cluster- and strain-specific genes that suggest major differences in ecological preferences and redefines the spectrum of disease-associated virulence factors. The results of the study indicate that particular clones of P. acnes play an etiologic role in acne while others are associated with health.

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          Genome analysis of multiple pathogenic isolates of Streptococcus agalactiae: implications for the microbial "pan-genome".

          The development of efficient and inexpensive genome sequencing methods has revolutionized the study of human bacterial pathogens and improved vaccine design. Unfortunately, the sequence of a single genome does not reflect how genetic variability drives pathogenesis within a bacterial species and also limits genome-wide screens for vaccine candidates or for antimicrobial targets. We have generated the genomic sequence of six strains representing the five major disease-causing serotypes of Streptococcus agalactiae, the main cause of neonatal infection in humans. Analysis of these genomes and those available in databases showed that the S. agalactiae species can be described by a pan-genome consisting of a core genome shared by all isolates, accounting for approximately 80% of any single genome, plus a dispensable genome consisting of partially shared and strain-specific genes. Mathematical extrapolation of the data suggests that the gene reservoir available for inclusion in the S. agalactiae pan-genome is vast and that unique genes will continue to be identified even after sequencing hundreds of genomes.
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            eBURST: inferring patterns of evolutionary descent among clusters of related bacterial genotypes from multilocus sequence typing data.

            The introduction of multilocus sequence typing (MLST) for the precise characterization of isolates of bacterial pathogens has had a marked impact on both routine epidemiological surveillance and microbial population biology. In both fields, a key prerequisite for exploiting this resource is the ability to discern the relatedness and patterns of evolutionary descent among isolates with similar genotypes. Traditional clustering techniques, such as dendrograms, provide a very poor representation of recent evolutionary events, as they attempt to reconstruct relationships in the absence of a realistic model of the way in which bacterial clones emerge and diversify to form clonal complexes. An increasingly popular approach, called BURST, has been used as an alternative, but present implementations are unable to cope with very large data sets and offer crude graphical outputs. Here we present a new implementation of this algorithm, eBURST, which divides an MLST data set of any size into groups of related isolates and clonal complexes, predicts the founding (ancestral) genotype of each clonal complex, and computes the bootstrap support for the assignment. The most parsimonious patterns of descent of all isolates in each clonal complex from the predicted founder(s) are then displayed. The advantages of eBURST for exploring patterns of evolutionary descent are demonstrated with a number of examples, including the simple Spain(23F)-1 clonal complex of Streptococcus pneumoniae, "population snapshots" of the entire S. pneumoniae and Staphylococcus aureus MLST databases, and the more complicated clonal complexes observed for Campylobacter jejuni and Neisseria meningitidis.
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              Multilocus sequence typing: a portable approach to the identification of clones within populations of pathogenic microorganisms.

              Traditional and molecular typing schemes for the characterization of pathogenic microorganisms are poorly portable because they index variation that is difficult to compare among laboratories. To overcome these problems, we propose multilocus sequence typing (MLST), which exploits the unambiguous nature and electronic portability of nucleotide sequence data for the characterization of microorganisms. To evaluate MLST, we determined the sequences of approximately 470-bp fragments from 11 housekeeping genes in a reference set of 107 isolates of Neisseria meningitidis from invasive disease and healthy carriers. For each locus, alleles were assigned arbitrary numbers and dendrograms were constructed from the pairwise differences in multilocus allelic profiles by cluster analysis. The strain associations obtained were consistent with clonal groupings previously determined by multilocus enzyme electrophoresis. A subset of six gene fragments was chosen that retained the resolution and congruence achieved by using all 11 loci. Most isolates from hyper-virulent lineages of serogroups A, B, and C meningococci were identical for all loci or differed from the majority type at only a single locus. MLST using six loci therefore reliably identified the major meningococcal lineages associated with invasive disease. MLST can be applied to almost all bacterial species and other haploid organisms, including those that are difficult to cultivate. The overwhelming advantage of MLST over other molecular typing methods is that sequence data are truly portable between laboratories, permitting one expanding global database per species to be placed on a World-Wide Web site, thus enabling exchange of molecular typing data for global epidemiology via the Internet.
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                Author and article information

                Contributors
                Role: Editor
                Journal
                PLoS One
                plos
                plosone
                PLoS ONE
                Public Library of Science (San Francisco, USA )
                1932-6203
                2010
                19 August 2010
                : 5
                : 8
                : e12277
                Affiliations
                [1]Department of Medical Microbiology and Immunology, Aarhus University, Aarhus, Denmark
                Charité-Universitätsmedizin Berlin, Germany
                Author notes

                Conceived and designed the experiments: HBL MK. Performed the experiments: HBL MK. Analyzed the data: HBL MK. Wrote the paper: HBL MK. Examined the subjects and collected the samples: HBL.

                Article
                10-PONE-RA-19854
                10.1371/journal.pone.0012277
                2924382
                20808860
                72df22ad-9c16-4099-aa14-7510d8157792
                Lomholt, Kilian. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
                History
                : 15 June 2010
                : 4 July 2010
                Page count
                Pages: 10
                Categories
                Research Article
                Genetics and Genomics/Population Genetics
                Microbiology/Medical Microbiology
                Dermatology/Acne-Like Disorders
                Infectious Diseases/Bacterial Infections
                Dermatology/Acne-Like Disorders
                Microbiology/Medical Microbiology

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                Uncategorized

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